Recently, voice-based digital assistants, such as Apple's SIRI, Amazon's Echo, Google's Google Assistant, and Microsoft's Cortana, have been introduced into the marketplace to handle various tasks such as home appliance controls, web search, calendaring, reminders, etc. One advantage of such voice-based digital assistants is that users can interact with an appliance in a hands-free manner without handling or even looking at the appliance. Conventionally, to initiate the voice-based digital assistant, users speak a trigger phase (e.g., a predefined wake-up word or command) to the voice-based digital assistant, or interacts with a user device (e.g., by opening an application on a smartphone and pressing virtual buttons on the user interface) that is coupled to control the voice-based digital assistant. The voice-based digital assistant interprets the voice command it receives after it has been activated, and performs an action (e.g., providing an informational answer and/or sending an encoded instruction to control a peripheral device, such as an appliance in a smart home environment).
However, controlling multiple appliances using conventional voice-based digital assistants pose many limitations. For example, conventional voice-based digital assistants are not power efficient because they require constant listening to speech command in the environment. Conventional voice-based digital assistants also require connection to the internet to access a server for complex and powerful natural language processing (NLP). However, internet accessibility not only requires certain hardware and software integrated on the digital assistants, but also brings privacy concerns to the user. Further, conventional voice-based digital assistants work with complex NLP models that are capable of handling a wide range of speech command. However, such complex NLP models are difficult and time-consuming to train and upgrade, and the accuracy and efficiency of using such complex NLP models are compromised. Moreover, conventional voice-based digital assistants do not provide sufficient mobility to accommodate user's needs to control multiple appliances while doing all kinds of activities at various locations within a certain environment (e.g., at home). Even if a user device (e.g., a smartphone) can be used to control the voice-based digital assistant, the user still has to interact with the user device to send command to the voice-based digital assistant, which is inconvenient and inefficient especially when the user is engaged in various activities. In addition, conventional voice-based digital assistants are proprietary and may be used only with appliances of expensive high-end models and/or appliances made by designated manufacturer(s).
Thus, it would be beneficial to provide portable NLP interface to improve the way that multiple appliances are controlled.